November 2006

Prediction Model Template from OHTS-EGPS Pooled Analyses

Today’s version is November 14

November 2006

A Prediction Model for Managing Ocular Hypertensive Patients

Presenter Name

The Ocular Hypertension Treatment Study Group (OHTS)National Eye Institute, National Center for Minority Healtlh and Health

Disparities, NIH grants EY 09307, EY09341, EY015498, Unrestricted Grant from Research to Prevent Blindness, Merck Research Laboratories

and Pfizer, Inc.

The European Glaucoma Prevention Study (EGPS)

European Commission BMH4-CT-96-1598 and Merck Research Laboratories

November 2006

Ocular hypertension

Ocular hypertension occurs in 4%-8% of people in the United States over age 40 (3-6 million people)

The number of affected people will increase with the aging of the population

Associated with large costs for patient examinations, tests and treatment

November 2006

Ocular hypertension

Elevated IOP is a leading risk factor for development of POAG

Only modifiable risk factor for POAG

Patients can lose a substantial proportion of their nerve fiber layer before POAG is detected by standard clinical tests

Quigley HA, et al. Arch Ophthal 1981;99:635

November 2006

Why do we need a prediction model?

2002 OHTS publication showed that early treatment reduces the incidence of POAG by more than 50%

However, only 1% of ocular hypertensive individuals develop POAG per year

Clear that treating all ocular hypertensive patients is neither medically nor economically justified

November 2006

Why do we need a prediction model?

Common in the past to base management decisions on a single predictive factor – usually IOP

What level of IOP do you treat?– IOP 24 mmHg?– IOP 26 mmHg?– IOP 28 mmHg?– IOP 30 mmHg?

This approach ingores other important predictive factors

November 2006

Why do we need a prediction model?

A prediction model stratifies ocular hypertensive individuals by level of risk

– To guide the frequency of visits and tests– To ascertain the benefit of early treatment

November 2006

In 2002, the Ocular Hypertension Treatment Study (OHTS) published a prediction model for POAG based on...

– Data from 1,636 ocular hypertensive participants randomized to either observation or topical hypotensive medication

– Median follow-up 6.6 years

Gordon et al, Arch Ophthalmol. 2002; 120: 714-720.

November 2006

Factors predictive for the development of POAG

in 2002 OHTS model 5 baseline factors increased the risk of developing

POAG

– Older age– Higher Intraocular pressure– Thinner central cornea– Larger vertical cup/disc ratio by contour– Higher pattern standard deviation

Diabetes decreased the risk of POAG

.

November 2006

2002 OHTS model needed to be confirmed

in a large, independent sample

2002 prediction model based on data from treated and untreated ocular hypertensive individuals – A prediction model should be based solely on untreated

individuals

OHTS sample included 25% African American participants– Is the prediction model valid in other groups?

OHTS was 1st study to report central cornea thickness as a powerful predictor of POAG– Can this finding be confirmed?

November 2006

A large indepent sample available through the European Glaucoma Prevention Study (EGPS)

– EGPS is a randomized clinical trial of 1,077 ocular hypertensive individuals randomized to either placebo or dorzolamide

– Median follow-up 4.8 years

November 2006

Purpose of collaboration with EGPS

To test the 2002 OHTS prediction model for the development of glaucoma in a large, independent sample

Before undertaking a collaboration with EGPS, the two study protocols were compared

November 2006

Comparison of OHTS and EGPS: Study design

*Similarities between OHTS and EGPS

OHTS EGPSStudy Design Unmasked

randomized clinical trial

Double masked randomized clinical trial

Large Sample 1,636 participants

22 clinics in United States

1,077 participants

18 clinics in 4 countries

Randomization

Groups

Observation

Any commercially available medication

Placebo

Dorzolamide

POAG Endpoint

Masked endpoint ascertainment

Masked endpoint ascertainment

November 2006

Collaborative analysis uses data only from participants not receiving medication:

– OHTS Observation Group n=819

– EGPS Placebo Group n=500

November 2006

OHTS vs EGPS: Eligibility criteria *Similarities between OHTS and EGPS

OHTS EGPS

Age (years) 40-80 inclusive > 30

Ocular eligibility criteria

Both eyes needed to meet all criteria

Both eyes required to meet all criteria except only one eye needed to meet IOP criterion

21% of EGPS participants had one eye ineligible because of IOP below entry criterion.

Collaborative analysis was repeated including and excluding participants enrolled with one eye eligible

November 2006

OHTS vs EGPS: Eligibility criteria *Similarities between OHTS and EGPS

OHTS EGPS

Normal optic discs

Clinical exam

Review of stereophotos by masked readers

Similar

Normal and reliable visual fields

Humphrey 30-2 Visual Fields

Masked readers

Humphrey 30-2 Visual Fields

Octopus 32-2 Visual Fields

Masked readers

20% of EGPS participants were tested using Octopus 32-2 visual fields. Octopus loss variance and mean defect were converted to Humphrey pattern standard deviation and mean deviation (Anderson et. al., 1999).

November 2006

OHTS vs EGPS: Exclusion criteria *Similarities between OHTS and EGPS

OHTS EGPS

Ocular exclusions

Excluded pigmentary dispersion syndrome and pseudoexfoliation

Included pigmentary dispersion syndrome and pseudoexfoliation

Collaborative analysis excluded EGPS participants (19 placebo participants) with pigmentary dispersion syndrome or pseudoexfoliation.

November 2006

OHTS vs EGPS: Corneal thickness measurement

*Similarities between OHTS and EGPS

OHTS EGPS

Central corneal thickness measurements

DGH 500 Ultrasound mean of 5 measurements

Identical

November 2006

OHTS vs EGPS: POAG endpoint criteria

*Similarities between OHTS and EGPS

OHTS EGPS

Definition of abnormality

3 consecutive VFs with PSD < 0.05 or GHT < 0.01

Or

2 consecutive stereophotographs showing deterioration

3 consecutive VFs with visual field defects

Or

1 stereophotograph showing deterioration

Confirmation of abnormality

Masked readers Masked readers

Attribution of abnormality to POAG

Masked

Endpoint Committee

Masked

Endpoint Committee

November 2006

Collaborative analysis is feasible

OHTS and EGPS protocols are similar enough to test the validity of the prediction model after resolution of study differences

Different enough in measures, geographic distribution and patient characteristics to test the generalizability of the OHTS prediction model

November 2006

Baseline Factors

OHTSObservation

Group

n=819

EGPS

PlaceboGroup

n=500

Female 58% 52%

Mean Age (Years) 55.7 + 9.7 57.7+10.2

RaceAfrican originCaucasian/other

25.2%

74.8%

0%100%

Median follow-up 6.6 yrs 4.8 yrs

ResultsOHTS vs EGPS control groups:

Baseline characteristics(Univariate analyses)

November 2006

ResultsOHTS vs EGPS control groups:

Definition of baseline IOP (mmHg)

OHTS Observation Group EGPS Placebo Group

Original definition of baseline IOP (mm Hg)

2-3 IOPs at Randomization Visit

24.9 + 2.7 SD

2-3 IOPs at 1 Eligibility Visit

23.5 + 1.7 SD

New definition of baseline IOP(mm Hg)

4-6 IOPs at 2 Qualifying Visits

plus

2-3 IOPs at Randomization Visit

Mean of 2 eyes

25.1 + 2.0 SD

2-3 IOPs at 1 Eligibility Visit

plus

1 IOP at 6 month visit

Mean of 1 or 2 eyes

22.4 + 2.0 SD

New definition of baseline IOP used data from 2-3 visits and improved estimate of baseline IOP.

November 2006

Baseline Factors

OHTSObservation

Mean + S.D.

Average of 2 eyes

EGPSPlacebo

Mean + S.D.

Average of 2 eyes or value of one eye

New baseline IOP mmHg 25.1 + 2.0 22.4 + 2.0

Vertical C/D ratio by contour 0.39 + 0.19 0.32 + 0.14

CCT (µm) 574.3 + 37.8 571.6 + 35.9

PSD (dB) 1.90 + 0.21 2.02 + 0.55

OHTS vs EGPS control groups: Baseline characteristics

November 2006

Outcome

OHTSObservation Group

N=819

EGPSPlacebo Group

N=500

Total POAG(Incidence per year)

104 POAG of 819

1.9% per year

61 POAG of 500

2.5% per year

Detection Method

Visual field only 33 32% 37 60.7%

Disc only 56 54% 24 39.3%

Visual field & disc

at same visit

15 14% 0 0.0%

OHTS vs EGPS control groups: 1st eye to develop POAG endpoint

November 2006

Why was the incidence of POAG higher in EGPS than in OHTS?

Differences in entry criteria

Differences in POAG endpoint criteria

Differences in risk characteristics of participants

November 2006

Steps in testing the validity of the OHTS prediction model

1. Perform separate analyses of OHTS Observation Group and EGPS Placebo Group

(Multivariate Cox proportional hazards models)

2. Compare results of the two analyses

November 2006

Results of independent multivariate analyses OHTS vs EGPS:

Separate predictive models in OHTS and in EGPS identified the same 5 predictors for POAG

AgeIOPCCTPSDVertical cup/disc ratio by contour

The predictive factors in the OHTS model and the EGPS model have similar hazard ratios

All comparisons of hazard ratios by t-test, p values > 0.05D’Agostino et al., JAMA;2001: 180-187

November 2006

Age Decade EGPS

OHTS

Multivariate Hazard Ratios for

OHTS Observation group and EGPS Placebo group

IOP (mm Hg) EGPS

OHTS

CCT (40 µm decrease) EGPS

OHTS

Vertical CD ratio EGPS

by contour OHTS

PSD (per 0.2 dB increase) EGPS

OHTS

1.37 (1.00, 1.88)

1.16 (0.94, 1.43)

HR 95% CI

1.11 (0.98,1.27)

1.21 (1.11, 1.31)

2.07 (1.49, 2.87)

2.00 (1.59, 2.50)

1.27 (1.04,1.54)

1.26 (1.12, 1.41)

1.05 (0.95, 1.16)

1.16 (0.95,1.41)

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

November 2006

OHTS prediction model for POAG is confirmed in EGPS

Prediction model is validated...– In an independent European study population – In ocular hypertensive individuals

not on treatment

Thinner central corneal measurement is confirmed as a predictive factor for POAG

November 2006

Next step was to pool OHTS and EGPS data in the same prediction model

To increase the sample size to 1,319 participants (165 POAG endpoints)

To tighten 95% confidence intervals for estimates of hazard ratios for POAG

November 2006

Age Decade EGPS

OHTS

Pooled

Multivariate Hazard RatiosOHTS Observation Group, the EGPS Placebo Group

Pooled OHTS and EGPS dataset

IOP (mm Hg) EGPS

OHTS Pooled

CCT (40 µm decrease) EGPS

OHTS

Pooled

Vertical CD Ratio (per 0.1 increase) EGPS

OHTS

Pooled

PSD (per 0.2 dB increase) EGPS

OHTS

Pooled

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

November 2006

Factors not in the prediction model: Heart disease

In univariate analyses, history of heart disease was a significant predictive factor in OHTS but not in EGPS

In multivariate analyses, heart disease was not a significant predictive factor in OHTS, EGPS or the pooled sample

November 2006

Factors not in the prediction model: Diabetes

History of diabetes reduced the risk of developing POAG in the 2002 OHTS prediction model

The effect of diabetes was difficult to estimate in current OHTS models – data based solely on self-report

Diabetes was not significant in univariate or multivariate EGPS prediction models

Because of poor statistical estimation, diabetes was not included in the final prediction models

November 2006

Which model performs best?

A model averaging data from both eyes?

A model using data from the worst eye?

A model using data from both eyes including asymmetry between the eyes?

These models all perform similarly and correlation coefficients ranging from 0.94 – 0.98.

November 2006

The OHTS and EGPS pooled data were reanalyzed using tree analyses to look for predictive factors that might be missed in

Cox model

Results from tree analyses– Identified the same 5 predictive factors

for POAG (Age, IOP, CCT, Vertical C/D, PSD)

– Confirmed that heart disease, diabetes, hypertension, myopia and self-identified race had no detectable effect on risk of developing POAG

November 2006

How accurate is the OHTS-EGPS prediction model for POAG?

The accuracy of prediction models in discriminating between patients who do and do not develop a disease is measured using the C statistic

C statistic ranges from 0.50 (random agreement) to 1.00 (perfect agreement)

November 2006

Accuracy of prediction models for POAG compared to Framingham Heart Study*

Prediction Models C-statistic

*Framingham Heart Study prediction model applied to different studies

0.63 - 0.83

OHTS observation group 0.76

EGPS placebo group 0.73

Pooled OHTS EGPS sample 0.74

D’Agostino et al. JAMA, 2001.

November 2006

Comparision of observed vs. predicted 5 year incidence of POAG for the OHTS-EGPS pooled sample

Decile of Predicted Risk (112 participants per decile)

Observed PredictedP

roba

bilit

y

0.00

0.04

0.08

0.12

0.16

0.20

0.24

0.28

0.32

0.36

1 2 3 4 5 6 7 8 9 10

November 2006

Using the prediction model

Available on web free of charge  https://ohts.wustl.edu/risk

Home Page

November 2006

Benefits of risk stratification to clinicians and patients

Decide on frequency of visits and tests

Ascertain the benefit of early treatment

Potentially reduce medical costs

November 2006

Cost Utility Analysis

Kymes et. al.*, reported that it was cost effective to treat ocular hypertensive individuals with > 2% per year risk of developing POAG

*Kymes et al., AJO, 2006;141: 997-1008.

November 2006

Approximately 30%-40% of the participants in the pooled sample have <1% per year risk of developing POAG

Many of these individuals could be seen and tested once a year

Most of these individuals do not require treatment

Potential cost savings

Benefits of risk stratification

November 2006

LIMITATIONS AND CAUTIONS

There is no guarantee that the predicted risk is accurate for a specific patient.

The predictions are more likely to be accurate for patients who are similar to the patients studied in the OHTS and the EGPS, and if your testing protocols for your patients resemble those used in the studies.

The model predicts the development of early POAG. It is not clear whether the model also predicts progression of established disease or the development of visual disability.

The model is based on baseline parameters. Changes during follow-up will alter the risk of developing POAG.

November 2006

Limitations and Cautions: Application of prediction models to individual patients

must include information outside the model

THE PREDICTIONS ARE DESIGNED TO AID BUT NOT TO REPLACE CLINICAL JUDGMENT.

Need to consider factors such as health status, life expectancy and patient preferences

– An 18 year old ocular hypertensive with a low 5-year risk of developing POAG might be a candidate for treatment

– A seriously ill 63 year old ocular hypertensive with a high 5-year risk of developing POAG might not be a candidate for treatment

November 2006

Summary

5 baseline factors accurately stratify ocular hypertensive individuals by their risk for developing POAG: – Age– IOP– Central corneal thickness– PSD– Vertical cup/disc ratio by contour

November 2006

Summary OHTS prediction model for POAG has

demonstrated high external validity

– OHTS model validated in EGPS sample and Diagnostic Innovations in Glaucoma Study sample (Medeiros FA, et al., Archives of Ophthalmology, 2005.)

– Model accurately predicts development of POAG in ocular hypertensive individuals not on treatment.

– Predictive model is accurate in self-identified whites and African Americans

November 2006

Next Steps Clarify the effects of diabetes, cardiovascular disease, ethnic

origin, myopia and family history of glaucoma on the risk of developing POAG

Test the generalizability of the predictive model in other populations

Add new diagnostic technology– Quantitative assessments of disc and nerve fiber layer parameters– Psychophysical tests

Identify new predictive factors– Diet– Environmental exposures– Genetic factors

Predictive models will evolve with new information

November 2006

Collaborative Group

Ocular Hypertension Treatment Study

Mae Gordon Michael Kass Phil Miller Julie Beiser Feng Gao Ralph D’Agostino

– Consulting Statistician, Boston University

European Glaucoma Prevention Study

Valter Torri Stefano Miglior Irene Floriani Davide Poli Ingrid Adamsons

OHTS Clinical Centers Bascom Palmer Eye Institute Eye Consultants of Atlanta Eye Physicians and Surgeons Cullen Eye Institute Devers Eye Institute Emory Eye Institute Henry Ford Hospitals Johns Hopkins University Krieger Eye Institute Howard University University of Maryland University of California, Los

Angeles Charles Drew University Kellogg Eye Center Kresge Eye Institute Great Lakes Eye Institute University of Louisville

Mayo Clinic New York Eye & Ear Infirmary Ohio State University Ophthalmic Surgeons & Consultants Pennsylvania College of Optometry MCP/Hahnemann University Scheie Eye Institute Keystone Eye Associates University of California, Davis University of California, San Diego University of California, San

Francisco University Suburban Health Center University of Ophthalmic Consultants Washington Eye Physicians &

Surgeons Eye Associates of Washington, DC Washington University, St. Louis

November 2006

EGPS Clinical CentersBelgium University of Antwerpen University of Buxelles University of Gent

Germany University of Leuven University of Mainz University of Freiburg University of Heidelberg University of Wuerzburg

Portugal Coimbra, AIBILI Viseu, S. Teotonio Hospital Lisbon, S. Jose’ Hospital

Italy University of Milan, S. Paolo

Hospital University of Milan, L. Sacco

Hospital University of Verona University of Parma Oftalmico Hospital, Rome S. Giovanni Hospital, Rome Fatebenefratelli Hospital, Rome